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Lung disease has been reported by World Health Organization (WHO) to have caused 2.77% of total death in Malaysia and is the 6th main cause of death which includes interstitial lung disease (ILD). ILD causes alteration and fibrosis in the lungs leading to breathing complications and can be diagnosed and analyzed using high resolution computed tomography (HRCT). Previous study has developed a robust...
In the field of histopathology, computer-assisted diagnosis systems are important in obtaining patient-specific diagnosis for various diseases and help define precision medicine. Therefore, many studies on automatic analysis methods for digital pathology images have been reported. One of the severe brain tumors is the Glioma can provide unique insights into identifying and grading disease stages....
Gram staining is a traditional bacteriological laboratory technique, which has widely usage on many medical research and application. However, gram staining reading is a time consumption work. In this paper, we employ Convolutional Neural Network method to design a classifier, by which gram staining images can be identified as normal group and disease model group effectively and correctly. And image...
Microbubble based contrast-enhanced ultrasound (CEUS) enables the visualization of vascularity given the tendency of microbubbles to function as a blood pooling agent. Using contrast specific ultrasound (US) imaging, it is possible to quantify the kinetics of these agents and derive various perfusion metrics. In this ongoing clinical study, we evaluate the feasibility of using these microbubble based...
To acquire reliable medical ultrasound images and accurately detect vascular diseases, it is inevitable to improve axial resolution and contrast facilitating clearly definition of depth and thickness of blood vessel walls.
Plane-wave imaging has been demonstrated in humans for cardiovascular (CV) studies, but its use in mouse embryo models has received minimal attention even though the mouse is the most common experimental organism to study gene function and human disease, including CV disease (CVD). While high-frequency ultrasound Doppler modes have been used to study mouse embryo models, traditional linear-array imaging...
Malaria is one of the leading causes of death, especially in high-risk groups die infants, toddlers, and pregnant women. In the world of almost 1 million people die because of it every year. Malaria is transmitted by the bite of a female Anopheles mosquito vectors that have been infected by Plasmodium. Identification of Plasmodium in the blood is done by visual observation blood cells using a microscope...
The Human Genome Project is kept captured the imagination of scientist, and still needs a lot of study and exploration. The study of the human genome will help in solving a lot of medical, psychological and criminal problems. It can use ancillary investigations for diagnosis of genetic diseases and to know the ability of someone to acquire disease and what type of food that suits him. The human body...
Malaria is a disease caused by parasitice protozoa belonging of the genus Plasmodium through the mediation of prick (bite) of Anopheles. Indonesia is one of the countries that has a high endemicity. There are four types of plasmodium that can cause malaria, which are plasmodium falciparum, plasmodium vivax, plasmodium oval and plasmodium malariae. One of the common ways to detect malaria parasites...
In this paper, we propose the first deep reinforce-ment learning framework to estimate the optimal Dynamic Treat-ment Regimes from observational medical data. This framework is more flexible and adaptive for high dimensional action and state spaces than existing reinforcement learning methods to model real life complexity in heterogeneous disease progression and treatment choices, with the goal to...
The chest X-ray is one of the most commonly accessible radiological examinations for screening and diagnosis of many lung diseases. A tremendous number of X-ray imaging studies accompanied by radiological reports are accumulated and stored in many modern hospitals Picture Archiving and Communication Systems (PACS). On the other side, it is still an open question how this type of hospital-size knowledge...
Chest radiography (chest X-ray) is a low-cost yet effective and widely used medical imaging procedures. The lacking of qualified radiologist seriously limits the applicability of the technique. We explore the possibility of designing a computer-aided diagnosis for chest X-rays using deep convolutional neural networks. Using a real-world dataset of 16,000 chest X-rays with natural language diagnosis...
Cardiovascular diseases (CVD) are the leading cause of death worldwide, and every year more people die of these diseases. Aiming to assist medical diagnoses through Computerized Tomography (CT) scans, this work proposes a new approach to segment CT images of the brain damaged by stroke. The proposed method takes into account two improvements of the level set method based on the likelihood of Normal...
Non-Alcohol Liver Disease (NAFLD) is nowadays the most common liver disease in Western Countries. It is the chronic condition of fat expansion in liver, which is not associated with alcohol consumption. Quantitating steatosis in liver biopsies could provide objective measurement of the severity of the disease, instead of using semi-quantitative scoring systems. The current work, introduces an automated...
Data science methods have the potential to benefit other scientific fields by shedding new light on common questions. One such task is help to make predictions on medical data. Diabetes mellitus or simply diabetes is a disease caused due to the increase level of blood glucose. Various traditional methods, based on physical and chemical tests, are available for diagnosing diabetes. The methods strongly...
Content Based Image Retrievals has become the most abbreviated thrust area today. The article we propose is a methodology for identifying the images based on relevancy using Kullback-Leibler method together with Generalized Gamma mixture model. The experimentation is carried out on the medical dataset namely med.univ-rennes1.fr and the results derived are compared for accuracy in terms of better perception...
Different approaches in Image Processing are widely used in the field of medicine and since health is the factor being considered, it must be vigilantly done. This study aims to develop a system that will apply the different techniques of Image Processing and Genetic Algorithm, specifically in automating the detection of Leukemia. The benchmarks in detecting Leukemia that are being used by the medical...
Interstitial fibrosis in renal biopsies has shown a good correlation to the presence of chronic kidney disease, and it is therefore quantified by pathologists in the diagnosis of the disease. In the previous work, the developed automatic quantification system for the interstitial fibrosis was presented. It was based on the segmentation of tubular structures. This paper advances the development of...
Digital holographic microscopy is an ideal tool for 3-D cell imaging and characterization. It provides a host of cell parameters based on cell morphology and its temporal dynamics or time variation. These parameters can be used to study and quantify cell growth and cell physiology. When coupled with classification algorithms, this technique can also be used to identify and classify cells such as blood...
Multi-atlas based label fusionmethods have been successfully used for medical image segmentation. In the field of brain region segmentation, multi-atlas based methods propagate labels from multiple atlases to target image by the similarity between patches in target image and atlases. Most of existing multi-atlas based methods usually use intensity feature, which is hard to capture high-order information...
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